Entities such as professional athletes, politicians, musicians, actors and companies (generally referred to herein as a “celebrity”) receive large amounts of solicited and unsolicited correspondence such as mail, email or other communications. Answering such correspondence is a tedious, expensive, and time-consuming process. Companies have departments of employees dedicated to responding to these communications. For individuals such as politicians, athletes, politicians, musicians, actors and others, it is much harder to organize a concerted effort to answer the correspondence that they receive. For example, an estimated 75% of all sports related fan mail is left unanswered. Those athletes that do respond often pay family members, friends or webmasters to read and answer their mail.
Further, a celebrity that does respond to such correspondence often discards the correspondence after a response is written and fails to capitalize on an opportunity to collect data from the communication and analyze valuable information regarding the people interested in or concerned with that celebrity. Such information can be useful for tracking demographics of interested parties and creating targeted marketing efforts. Recent security concerns have created a new demand in the handling and analysis of correspondence. Such information can provide data to identify individuals who can be classified as a threat to the entity receiving the correspondence, such as, for example, a stalker.
One response in the prior art for handling such correspondence is to utilize personnel who manually review and handle correspondence received by individuals such as athletes, musicians, and actors. Various companies also offer such services. These companies utilize a manual process, responding to each letter by hand. While much information can be gleaned from this manual process, it is personnel intensive, time-consuming, inefficient and expensive. Further, results can be inconsistent since “relevant” data is based on the judgment of the individual reviewing a particular piece of correspondence. Another prior art response is to simply generate a generic response to such correspondence. In the case of such a generic response, no matter what kind of communication is received or the particular data contained in the communication, the sender will receive the same response. Such a response is likely to leave a correspondence sender unsatisfied. Moreover, such a response is not likely to be effective in collecting information about the sender.
There are no products in the prior art that can effectively provide such analysis. The database management and text-processing applications of the prior art tend only to enable users to locate key words within textual documents. For example, Microsoft Word enables users to search for key words and Oracle applications provide Boolean search tools to locate data. However, these prior art products are not capable of searching a database of correspondence, such as solicited or unsolicited mail, email and other communications, in order to effectively automate responses in a customized format based on individual correspondence content.
Thus, the prior art is unable to efficiently and effectively generate automatic, meaningful or “custom” response to correspondence, particularly significant amounts of correspondence. Furthermore, the prior art does not provide any means for deriving additional value from the inherent data found within databases formed of information extracted from such correspondence. Therefore, a need exists for a system and method for database development, data-mining and data-manipulation of correspondence send to receiving entities and customization of responses based on content or other terms contained in the correspondence as defined by the receiving entity. Such a system should include an effective interface between an end user celebrity and the correspondence database that provides access to the correspondence and manipulation of the data collected therefrom.